[petsc-users] [External] Re: request to add an option similar to use_omp_threads for mumps to cusparse solver
Barry Smith
bsmith at petsc.dev
Wed Oct 13 18:53:28 CDT 2021
> On Oct 13, 2021, at 3:50 PM, Chang Liu <cliu at pppl.gov> wrote:
>
> Hi Barry,
>
> That is exactly what I want.
>
> Back to my original question, I am looking for an approach to transfer
> matrix
> data from many MPI processes to "master" MPI
> processes, each of which taking care of one GPU, and then upload the data to GPU to
> solve.
> One can just grab some codes from mumps.c to aijcusparse.cu.
mumps.c doesn't actually do that. It never needs to copy the entire matrix to a single MPI rank.
It would be possible to write such a code that you suggest but it is not clear that it makes sense
1) For normal PETSc GPU usage there is one GPU per MPI rank, so while your one GPU per big domain is solving its systems the other GPUs (with the other MPI ranks that share that domain) are doing nothing.
2) For each triangular solve you would have to gather the right hand side from the multiple ranks to the single GPU to pass it to the GPU solver and then scatter the resulting solution back to all of its subdomain ranks.
What I was suggesting was assign an entire subdomain to a single MPI rank, thus it does everything on one GPU and can use the GPU solver directly. If all the major computations of a subdomain can fit and be done on a single GPU then you would be utilizing all the GPUs you are using effectively.
Barry
>
> Chang
>
> On 10/13/21 1:53 PM, Barry Smith wrote:
>> Chang,
>> You are correct there is no MPI + GPU direct solvers that currently do the triangular solves with MPI + GPU parallelism that I am aware of. You are limited that individual triangular solves be done on a single GPU. I can only suggest making each subdomain as big as possible to utilize each GPU as much as possible for the direct triangular solves.
>> Barry
>>> On Oct 13, 2021, at 12:16 PM, Chang Liu via petsc-users <petsc-users at mcs.anl.gov> wrote:
>>>
>>> Hi Mark,
>>>
>>> '-mat_type aijcusparse' works with mpiaijcusparse with other solvers, but with -pc_factor_mat_solver_type cusparse, it will give an error.
>>>
>>> Yes what I want is to have mumps or superlu to do the factorization, and then do the rest, including GMRES solver, on gpu. Is that possible?
>>>
>>> I have tried to use aijcusparse with superlu_dist, it runs but the iterative solver is still running on CPUs. I have contacted the superlu group and they confirmed that is the case right now. But if I set -pc_factor_mat_solver_type cusparse, it seems that the iterative solver is running on GPU.
>>>
>>> Chang
>>>
>>> On 10/13/21 12:03 PM, Mark Adams wrote:
>>>> On Wed, Oct 13, 2021 at 11:10 AM Chang Liu <cliu at pppl.gov <mailto:cliu at pppl.gov>> wrote:
>>>> Thank you Junchao for explaining this. I guess in my case the code is
>>>> just calling a seq solver like superlu to do factorization on GPUs.
>>>> My idea is that I want to have a traditional MPI code to utilize GPUs
>>>> with cusparse. Right now cusparse does not support mpiaij matrix, Sure it does: '-mat_type aijcusparse' will give you an mpiaijcusparse matrix with > 1 processes.
>>>> (-mat_type mpiaijcusparse might also work with >1 proc).
>>>> However, I see in grepping the repo that all the mumps and superlu tests use aij or sell matrix type.
>>>> MUMPS and SuperLU provide their own solves, I assume .... but you might want to do other matrix operations on the GPU. Is that the issue?
>>>> Did you try -mat_type aijcusparse with MUMPS and/or SuperLU have a problem? (no test with it so it probably does not work)
>>>> Thanks,
>>>> Mark
>>>> so I
>>>> want the code to have a mpiaij matrix when adding all the matrix terms,
>>>> and then transform the matrix to seqaij when doing the factorization
>>>> and
>>>> solve. This involves sending the data to the master process, and I
>>>> think
>>>> the petsc mumps solver have something similar already.
>>>> Chang
>>>> On 10/13/21 10:18 AM, Junchao Zhang wrote:
>>>> >
>>>> >
>>>> >
>>>> > On Tue, Oct 12, 2021 at 1:07 PM Mark Adams <mfadams at lbl.gov
>>>> <mailto:mfadams at lbl.gov>
>>>> > <mailto:mfadams at lbl.gov <mailto:mfadams at lbl.gov>>> wrote:
>>>> >
>>>> >
>>>> >
>>>> > On Tue, Oct 12, 2021 at 1:45 PM Chang Liu <cliu at pppl.gov
>>>> <mailto:cliu at pppl.gov>
>>>> > <mailto:cliu at pppl.gov <mailto:cliu at pppl.gov>>> wrote:
>>>> >
>>>> > Hi Mark,
>>>> >
>>>> > The option I use is like
>>>> >
>>>> > -pc_type bjacobi -pc_bjacobi_blocks 16 -ksp_type fgmres
>>>> -mat_type
>>>> > aijcusparse *-sub_pc_factor_mat_solver_type cusparse
>>>> *-sub_ksp_type
>>>> > preonly *-sub_pc_type lu* -ksp_max_it 2000 -ksp_rtol 1.e-300
>>>> > -ksp_atol 1.e-300
>>>> >
>>>> >
>>>> > Note, If you use -log_view the last column (rows are the
>>>> method like
>>>> > MatFactorNumeric) has the percent of work in the GPU.
>>>> >
>>>> > Junchao: *This* implies that we have a cuSparse LU
>>>> factorization. Is
>>>> > that correct? (I don't think we do)
>>>> >
>>>> > No, we don't have cuSparse LU factorization. If you check
>>>> > MatLUFactorSymbolic_SeqAIJCUSPARSE(),you will find it calls
>>>> > MatLUFactorSymbolic_SeqAIJ() instead.
>>>> > So I don't understand Chang's idea. Do you want to make bigger
>>>> blocks?
>>>> >
>>>> >
>>>> > I think this one do both factorization and solve on gpu.
>>>> >
>>>> > You can check the runex72_aijcusparse.sh file in petsc
>>>> install
>>>> > directory, and try it your self (this is only lu
>>>> factorization
>>>> > without
>>>> > iterative solve).
>>>> >
>>>> > Chang
>>>> >
>>>> > On 10/12/21 1:17 PM, Mark Adams wrote:
>>>> > >
>>>> > >
>>>> > > On Tue, Oct 12, 2021 at 11:19 AM Chang Liu
>>>> <cliu at pppl.gov <mailto:cliu at pppl.gov>
>>>> > <mailto:cliu at pppl.gov <mailto:cliu at pppl.gov>>
>>>> > > <mailto:cliu at pppl.gov <mailto:cliu at pppl.gov>
>>>> <mailto:cliu at pppl.gov <mailto:cliu at pppl.gov>>>> wrote:
>>>> > >
>>>> > > Hi Junchao,
>>>> > >
>>>> > > No I only needs it to be transferred within a
>>>> node. I use
>>>> > block-Jacobi
>>>> > > method and GMRES to solve the sparse matrix, so each
>>>> > direct solver will
>>>> > > take care of a sub-block of the whole matrix. In this
>>>> > way, I can use
>>>> > > one
>>>> > > GPU to solve one sub-block, which is stored within
>>>> one node.
>>>> > >
>>>> > > It was stated in the documentation that cusparse
>>>> solver
>>>> > is slow.
>>>> > > However, in my test using ex72.c, the cusparse
>>>> solver is
>>>> > faster than
>>>> > > mumps or superlu_dist on CPUs.
>>>> > >
>>>> > >
>>>> > > Are we talking about the factorization, the solve, or
>>>> both?
>>>> > >
>>>> > > We do not have an interface to cuSparse's LU
>>>> factorization (I
>>>> > just
>>>> > > learned that it exists a few weeks ago).
>>>> > > Perhaps your fast "cusparse solver" is '-pc_type lu
>>>> -mat_type
>>>> > > aijcusparse' ? This would be the CPU factorization,
>>>> which is the
>>>> > > dominant cost.
>>>> > >
>>>> > >
>>>> > > Chang
>>>> > >
>>>> > > On 10/12/21 10:24 AM, Junchao Zhang wrote:
>>>> > > > Hi, Chang,
>>>> > > > For the mumps solver, we usually transfers
>>>> matrix
>>>> > and vector
>>>> > > data
>>>> > > > within a compute node. For the idea you
>>>> propose, it
>>>> > looks like
>>>> > > we need
>>>> > > > to gather data within MPI_COMM_WORLD, right?
>>>> > > >
>>>> > > > Mark, I remember you said cusparse solve is
>>>> slow
>>>> > and you would
>>>> > > > rather do it on CPU. Is it right?
>>>> > > >
>>>> > > > --Junchao Zhang
>>>> > > >
>>>> > > >
>>>> > > > On Mon, Oct 11, 2021 at 10:25 PM Chang Liu via
>>>> petsc-users
>>>> > > > <petsc-users at mcs.anl.gov
>>>> <mailto:petsc-users at mcs.anl.gov>
>>>> > <mailto:petsc-users at mcs.anl.gov
>>>> <mailto:petsc-users at mcs.anl.gov>> <mailto:petsc-users at mcs.anl.gov
>>>> <mailto:petsc-users at mcs.anl.gov>
>>>> > <mailto:petsc-users at mcs.anl.gov
>>>> <mailto:petsc-users at mcs.anl.gov>>>
>>>> > > <mailto:petsc-users at mcs.anl.gov
>>>> <mailto:petsc-users at mcs.anl.gov>
>>>> > <mailto:petsc-users at mcs.anl.gov
>>>> <mailto:petsc-users at mcs.anl.gov>> <mailto:petsc-users at mcs.anl.gov
>>>> <mailto:petsc-users at mcs.anl.gov>
>>>> > <mailto:petsc-users at mcs.anl.gov
>>>> <mailto:petsc-users at mcs.anl.gov>>>>>
>>>> > > wrote:
>>>> > > >
>>>> > > > Hi,
>>>> > > >
>>>> > > > Currently, it is possible to use mumps
>>>> solver in
>>>> > PETSC with
>>>> > > > -mat_mumps_use_omp_threads option, so that
>>>> > multiple MPI
>>>> > > processes will
>>>> > > > transfer the matrix and rhs data to the master
>>>> > rank, and then
>>>> > > master
>>>> > > > rank will call mumps with OpenMP to solve
>>>> the matrix.
>>>> > > >
>>>> > > > I wonder if someone can develop similar
>>>> option for
>>>> > cusparse
>>>> > > solver.
>>>> > > > Right now, this solver does not work with
>>>> > mpiaijcusparse. I
>>>> > > think a
>>>> > > > possible workaround is to transfer all the
>>>> matrix
>>>> > data to one MPI
>>>> > > > process, and then upload the data to GPU to
>>>> solve.
>>>> > In this
>>>> > > way, one can
>>>> > > > use cusparse solver for a MPI program.
>>>> > > >
>>>> > > > Chang
>>>> > > > --
>>>> > > > Chang Liu
>>>> > > > Staff Research Physicist
>>>> > > > +1 609 243 3438
>>>> > > > cliu at pppl.gov <mailto:cliu at pppl.gov>
>>>> <mailto:cliu at pppl.gov <mailto:cliu at pppl.gov>>
>>>> > <mailto:cliu at pppl.gov <mailto:cliu at pppl.gov>
>>>> <mailto:cliu at pppl.gov <mailto:cliu at pppl.gov>>>
>>>> > <mailto:cliu at pppl.gov <mailto:cliu at pppl.gov>
>>>> <mailto:cliu at pppl.gov <mailto:cliu at pppl.gov>>
>>>> > > <mailto:cliu at pppl.gov <mailto:cliu at pppl.gov>
>>>> <mailto:cliu at pppl.gov <mailto:cliu at pppl.gov>>>>
>>>> > > > Princeton Plasma Physics Laboratory
>>>> > > > 100 Stellarator Rd, Princeton NJ 08540, USA
>>>> > > >
>>>> > >
>>>> > > --
>>>> > > Chang Liu
>>>> > > Staff Research Physicist
>>>> > > +1 609 243 3438
>>>> > > cliu at pppl.gov <mailto:cliu at pppl.gov>
>>>> <mailto:cliu at pppl.gov <mailto:cliu at pppl.gov>> <mailto:cliu at pppl.gov
>>>> <mailto:cliu at pppl.gov>
>>>> > <mailto:cliu at pppl.gov <mailto:cliu at pppl.gov>>>
>>>> > > Princeton Plasma Physics Laboratory
>>>> > > 100 Stellarator Rd, Princeton NJ 08540, USA
>>>> > >
>>>> >
>>>> > --
>>>> > Chang Liu
>>>> > Staff Research Physicist
>>>> > +1 609 243 3438
>>>> > cliu at pppl.gov <mailto:cliu at pppl.gov> <mailto:cliu at pppl.gov
>>>> <mailto:cliu at pppl.gov>>
>>>> > Princeton Plasma Physics Laboratory
>>>> > 100 Stellarator Rd, Princeton NJ 08540, USA
>>>> >
>>>> -- Chang Liu
>>>> Staff Research Physicist
>>>> +1 609 243 3438
>>>> cliu at pppl.gov <mailto:cliu at pppl.gov>
>>>> Princeton Plasma Physics Laboratory
>>>> 100 Stellarator Rd, Princeton NJ 08540, USA
>>>
>>> --
>>> Chang Liu
>>> Staff Research Physicist
>>> +1 609 243 3438
>>> cliu at pppl.gov
>>> Princeton Plasma Physics Laboratory
>>> 100 Stellarator Rd, Princeton NJ 08540, USA
>
> --
> Chang Liu
> Staff Research Physicist
> +1 609 243 3438
> cliu at pppl.gov
> Princeton Plasma Physics Laboratory
> 100 Stellarator Rd, Princeton NJ 08540, USA
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